Modeling of an optimized electrostimulative hip revision system under consideration of uncertainty in the conductivity of bone tissue.

Since several years, the number of total hip arthroplasty revision surgeries is substantially growing. One of the main reasons for this procedure to become necessary is the loosening or damage of the prothesis, which is facilitated by bone necrosis at the implant-bone interface. Electrostimulation is one promising technique, which can accelerate the growth of bone cells and, therefore, enhance the anchorage of the implant to the bone. We present computational models of an electrostimulative total hip revision system to enhance bone regeneration. In this study, the influence of uncertainty in the conductivity of bone tissue on the electric field strength and the beneficial stimulation volume for an optimized electrode geometry and arrangement is investigated. The generalized polynomial chaos technique is used to quantify the uncertainty in the stimulation volumes with respect to the uncertain conductivity of cancellous bone, bone marrow, and bone substitute, which is used to fill defective areas. The results suggest that the overall beneficial stimulation areas are only slightly sensitive to the uncertainty in conductivity of bone tissue. However, in the proximity of tissue boundaries, larger uncertainties, especially in the transition between beneficial and understimulation areas, can be expected.

The impact of bone microstructure on the field distribution of electrostimulative implants.

Since the 1980s several methods of electrostimulative techniques have been developed to accelerate bone regeneration during orthopedic treatment. These techniques have proven to provide increased bone formation while curing fractures and bone diseases. The electric parameters, however, are mostly results of empiric research regarding the bone tissue as homogeneous material. Especially cancellous bone, which is the objective of a new electrostimulative total hip revision system, has a porous, inhomogeneous microstructure. The present work investigates numerically the electric field distribution within this tissue using microscopic computer tomography scans of small bone samples. The 3-dimensional X-ray absorption values of these scans are correlated with conductivity values from literature applying different correlation approaches. Compared to electric fields within a homogeneous material strong elevations can be observed within the structures which include most of the bone forming cells.

Linking a neural mass model with a 3D model of the human brain to reproduce EEG signals.

Electroencephalography (EEG) is often employed to measure electrical activity in the living human brain. Simulation studies can help unravel how the brain electrical activity pattern generates the EEG signal, still a widely unresolved question. This article describes a method to simulate brain electrical activity by using neuronal populations of a neural mass model. Implementing these populations in a finite element model of the head offers the opportunity to investigate the influence of each group of neurons to the scalp potential. This model is based on structural magnetic resonance imaging data to specify tissue composition, and diffusion tensor imaging data to model local anisotropy. We simulated the EEG signals of five neuronal populations generating α waves in the visual cortex. Our results indicate that radially oriented sources dominate over tangential sources in the generation of the scalp signal. Investigating the influence of anisotropic conductivity, we found small differences in topography and phase and larger ones for the potential amplitude compared with an isotropic conductivity distribution. The outcome of this article is a fast method based on superposition of sources for simulating time-dependent EEG signals, which can be used for further studies of neurodegenerative diseases.

Uncertainty quantification of the optimal stimulation area in an electro-stimulative hip revision system.

Electro-stimulative hip revision systems accelerate the bone growth around the implant and are capable of reducing the number of side effects such as aseptic implant loosening. A computational model was developed to determine the optimal electrode arrangement for such a system, which is currently under development. The optimization process depends on the electrical properties of bone material and the used bone substitute, which are subject to uncertainty in literature and its production process, respectively. To quantify the influence of these uncertain parameters on the optimal stimulation ratio (OSR), the computationally effective non-intrusive polynomial chaos technique was applied. The results indicate that the conductivity of bone substitute is most sensitive to the OSR, while its uncertainty was comparatively small compared to that of the uncertain parameters.

Identification of widely applicable configurations for the electrostimulative total hip revision system.

Since the 1980s electrostimulation is used to accelerate the healing of fractures and bone defects. In prior works this effect has been implemented in a numerical model of an electrostimulative hip revision cup which was optimized using a multi-objective evolutionary algorithm. The aim of our simulations is to design an implant which provides optimal electric fields in the acetabular region enhancing the reconstruction of the pelvic bone in such way as to improve the fixation of the prosthesis in the surrounding bone. In the present work we will show that this multi-objective algorithm can also be used to identify a small amount of configurations of the implant that will be able to stimulate a wide range of pelvic bones with different acetabular defects.